The birds at the center of the study were not commercial giants but Egyptian black Baladi turkeys, the country’s indigenous breed. Glossy black feathers, moderate body size, and a reputation for surviving harsh conditions and resisting local diseases make the Baladi a valuable reservoir of genetic diversity, even though its growth rate trails that of commercial strains. The breed has long been maintained through uncontrolled natural mating in backyard flocks across the Nile Delta and Upper Egypt, with selection based mainly on visible traits such as body weight, fertility, and survivability. No nationwide breeding or conservation program exists for the breed, which is precisely why the researchers, led by Mohamed H. Khalil of Alexandria University and Mostafa K. Shebl, wanted to quantify how much genetic progress structured selection could deliver.

The experiment began in 2019 at the Poultry Research Centre of Alexandria University, where 193 birds formed the randomly mated base population. From this flock, the heaviest birds at six months of age, 13 males and 55 females, were chosen as parents of a selected line, while a random-bred control line was maintained from the same base. Over the following generation, researchers recorded body weights at hatching and at every month through six months, along with shank length and breast width at six months. The birds were reared under identical floor-pen conditions with feed formulated to standard requirements at each growth stage, ensuring that any differences between the lines reflected genetics rather than management.

The numbers tell a clear story. At six months, selected-line turkeys averaged 4404.61 grams compared with 3967.25 grams in the control line, a statistically significant difference and the only age point where the lines diverged significantly. Regression analysis estimated average monthly growth of 768.03 grams in the selected line versus 710.67 grams in the control. Sex mattered enormously too: males at six months weighed 5599.07 grams on average against 3419.71 grams for females, a striking sexual dimorphism of roughly 63.7 percent. Shank length and breast width were also significantly greater in the selected line, confirming that selection for weight pulled skeletal and muscular dimensions along with it.

To predict future gains, the team constructed a selection index, a statistical tool that combines multiple traits into a single score weighted by heritability, genetic correlations, and economic value. Using the framework of Cunningham, they built an index from body weight, shank length, and breast width at six months, solving matrix equations involving the phenotypic and genetic variance-covariance matrices to derive the optimal weighting factors. The resulting index showed a correlation of 0.84 with the aggregate breeding value, a high accuracy that means the score ranks animals’ genetic merit reliably. The expected genetic gains per generation were substantial: 441.71 grams of body weight, 0.26 centimeters of shank length, and 1.93 centimeters of breast width.

Perhaps the most revealing finding came from dissecting which traits drove the index. Removing breast width from the calculation reduced overall genetic gain by 18.57 percent, the largest contribution of any trait, followed by body weight at 7.69 percent, while shank length contributed a mere 1.28 percent. The genetic correlation between body weight and breast width was an extraordinary 0.97, meaning the two traits are almost entirely controlled by the same genes. For breeders, this makes breast width an exceptionally reliable indirect criterion for improving meat yield, and it explains why the correlated response in body dimensions followed so faithfully from selection on weight alone.

Then came the molecular layer. The researchers sampled the Pectoralis major, the main breast muscle, from 18 birds across both lines and both sexes, extracting RNA and quantifying growth hormone mRNA using quantitative reverse transcription PCR, with beta-actin as the reference gene and the 2-delta-Ct method for normalization. Growth hormone, a polypeptide secreted by the pituitary gland, sits at the heart of the somatotropic axis that governs growth, muscle development, protein synthesis, fat metabolism, and even reproduction in poultry. The selected line showed significantly higher GH expression than the control in both sexes: a relative expression of 1.43 versus 1.01 in males, and 1.76 versus 1.31 in females. Intriguingly, females expressed more GH than males despite being far lighter, echoing earlier reports of sex differences in GH expression.

The authors are careful about what this association does and does not prove. Higher GH-mRNA expression in the selected line is consistent with the idea that molecular mechanisms underpin the phenotypic gains, but the study does not establish causation. The elevated expression may simply reflect the physiology of a heavier phenotype rather than a direct consequence of selection, and the researchers explicitly note that further work is needed to clarify the biology and to validate GH expression as a molecular indicator in breeding programs. Previous studies have linked GH gene polymorphisms and expression patterns to growth traits in chickens and quail, and earlier turkey research found that growth-selected lines showed higher hepatic growth hormone receptor binding, so the new results fit a broader pattern across poultry genetics.

For the Baladi breed, the practical implications are immediate. A selection index with 0.84 accuracy offers smallholder-oriented breeding programs a way to improve growth while preserving the breed’s adaptive traits, and the identification of breast width as the highest-value index trait gives breeders a concrete measurement to prioritize. The GH expression findings open a longer-term possibility: combining conventional phenotypic selection with molecular markers to accelerate gains in indigenous livestock, where genomic tools remain scarce. As global demand for poultry protein grows and indigenous breeds face pressure from commercial crosses, studies like this one show that the old tools of quantitative genetics and the new tools of gene expression can work together, weighing birds in the pen and reading their genes in the laboratory to chart a faster, more informed path of genetic improvement.

Subject of Research: Selection index prediction of genetic gain and growth hormone gene expression in Egyptian Baladi turkeys

Article Title: GH-mRNA expression and prediction of genetic improvement using selection index for body weight traits in turkeys

Article References: Khalil, M. H., Abd El-Motaleb, A. A., Abdel-Rahman, M. M., Amin, E. M., Abousoliman, I., & Shebl, M. K. (2026). GH-mRNA expression and prediction of genetic improvement using selection index for body weight traits in turkeys. Archives Animal Breeding, 69(3), 411-420. https://doi.org/10.5194/aab-69-411-2026

Image Credits: AI Generated

DOI: 10.5194/aab-69-411-2026

Keywords: turkeys, growth hormone, selection index, genetic improvement, body weight, Baladi, gene expression, qRT-PCR, poultry breeding, heritability, breast width, molecular marker

The team’s strategy rested on a classic tool of quantitative genetics: the recombinant inbred line population. Starting from a single cross between Svevo, an elite Italian durum wheat cultivar prized for its quality, and Zavitan, a wild emmer wheat accession originally collected in Israel, the researchers generated 135 recombinant inbred lines, or RILs. Each of these lines carries a unique mosaic of chromosome segments inherited from the two parents, produced through repeated self-pollination over multiple generations until the lines became genetically fixed. This means that every line is a stable, reproducible combination of Svevo and Zavitan DNA, allowing researchers to ask, for any given trait, which parental chromosome segments are associated with better performance.

To capture the traits that matter most for yield, the team measured four grain characteristics across four different environments: grain length, grain width, the ratio of length to width, and thousand-grain weight, a standard agronomic measure of how heavy an average sample of one thousand grains is. Evaluating the population in multiple environments is critical because grain traits are notoriously sensitive to growing conditions, and a genetic effect that appears in one field may vanish in another. Only loci that show consistent effects across environments, so-called stable quantitative trait loci or QTL, are truly useful for breeding, since breeders need markers that will deliver results regardless of where or when a variety is grown.

Genotyping the 135 lines was accomplished with the wheat 90K single nucleotide polymorphism array, a platform that interrogates tens of thousands of genetic markers spread across the wheat genome. Wheat is a challenging genome to work with: durum wheat carries two subgenomes, designated A and B, each contributing seven chromosome pairs, and the genome is enormous by any standard. The SNP array allowed the researchers to construct a linkage map and then scan the genome systematically for regions where the inheritance pattern of DNA markers correlated with the measured grain traits. Statistical mapping, using established QTL detection methods with empirical significance thresholds, then pinpointed the chromosomal intervals most likely to harbor genes influencing each trait.

The scan yielded eleven stable QTL, each detected consistently across the four test environments. These intervals ranged in physical size from 0.7 to 15.6 megabases on the durum wheat reference genome, a span that in some cases is small enough to narrow down candidate genes with reasonable confidence. Three of the stable loci, named QGLsv.swust-5AL, QGLsv.swust-5BL, and QGLsv.swust-7AL, influenced grain length; two, QGWsv.swust-4AL and QGWsv.swust-5AL, influenced grain width; and two, QTGWsv.swust-2BL and QTGWsv.swust-5BL, influenced thousand-grain weight. For all seven of these loci, the favorable allele, meaning the version of the gene region associated with larger or heavier grains, came from the cultivated parent Svevo, reflecting the cumulative effect of decades of selection by durum breeders.

The most intriguing finding, however, concerned the remaining four loci. All four QTL for grain length-width ratio, designated QLWRzv.swust-2BS, QLWRzv.swust-4AL, QLWRzv.swust-4BL, and QLWRzv.swust-6AS, carried their positive alleles from Zavitan, the wild parent. Grain shape, as captured by the length-to-width ratio, matters for both milling performance and market quality in durum wheat, and the fact that the wild ancestor consistently contributed the favorable alleles at these loci demonstrates that domestication did not exhaust the wild gene pool’s value. Wild emmer wheat, which grows naturally in the Fertile Crescent and has survived thousands of years of environmental fluctuation without human intervention, retains genetic variation that modern cultivars have lost, and this study shows that some of that variation is directly relevant to yield-related traits.

Quantitatively, the eleven stable QTL each explained between 9.22 and 19.22 percent of the phenotypic variation in their respective traits. These are substantial effects for complex agronomic traits, which are typically controlled by many genes of small effect. The fact that individual loci account for nearly a fifth of the variation in a trait like grain weight suggests that marker-assisted selection targeting these regions could produce measurable improvements in a breeding program. Marker-assisted selection, in which breeders use DNA markers rather than visible traits to track the inheritance of favorable genes, is particularly powerful for traits like grain weight that are difficult or expensive to measure directly on large numbers of early-generation plants.

To move from statistical associations to biological understanding, the researchers projected their QTL intervals onto three available reference genomes: Chinese Spring, the standard reference for bread wheat, and the Svevo and Zavitan genome assemblies for durum wheat. This cross-genome comparison identified 67 high-confidence candidate genes within the QTL intervals on the Chinese Spring reference, 88 on the Svevo reference, and 70 on the Zavitan reference. Functional annotation of these candidate genes revealed that they are enriched for roles in processes that make intuitive sense for grain development: seed development itself, transcriptional regulation, hormone signaling pathways, ubiquitin-mediated protein degradation, and carbohydrate metabolism. Each of these processes has well-documented connections to how a developing grain accumulates starch and protein and how large it ultimately grows.

The candidate gene list connects to a growing body of wheat functional genomics. Recent studies have identified genes such as TaSWEET11 and TaSWEET13h, sucrose transporters that are critical for grain filling, transcription factors like TaDOF6 that regulate sugar and gibberellin transport into the endosperm, and cytochrome P450 genes of the CYP78A family that influence seed size through hormone-mediated pathways. Several of the candidate genes identified in the new study fall into these same functional categories, suggesting that the mapped QTL may harbor orthologs or paralogs of genes whose effects have already been validated in bread wheat and rice. This convergence strengthens confidence that the mapped loci are not statistical artifacts but genuine biological regulators of grain development.

The practical implications extend beyond basic science. The stable QTL and their linked SNP markers constitute a direct resource for marker-assisted breeding in durum wheat, allowing breeders to introgress favorable alleles from wild emmer into elite backgrounds while simultaneously tracking the cultivated alleles that boost grain size and weight. Because the QTL were validated across four environments, breeders can have reasonable confidence that these markers will perform consistently across the diverse conditions in which durum wheat is grown, from the rain-fed fields of the Mediterranean to irrigated plains elsewhere. More broadly, the study reinforces a central lesson of modern crop improvement: the wild relatives of our staple crops are not relics of the past but living repositories of genetic variation, and interspecific crosses that tap into them can enrich the genetic basis of yield in ways that within-crop selection alone cannot achieve. As the global population grows and climate change pressures wheat production systems, tools like these that bridge the gap between wild genetic resources and elite cultivars will become increasingly indispensable.

Subject of Research: Mapping stable quantitative trait loci for grain yield-related traits in a durum wheat Svevo × Zavitan recombinant inbred line population

Article Title: Identification of stable QTL for yield-related traits in a durum wheat Svevo × Zavitan RIL population

Article References: Zhou, X., Zhou, B., Zhang, G., Zou, G., Yang, X., Xia, C., Li, X., Zheng, S., & Ren, Y. (2026). Identification of stable QTL for yield-related traits in a durum wheat Svevo × Zavitan RIL population. Theoretical and Applied Genetics, 139(10), Article 275. https://doi.org/10.1007/s00122-026-05389-1

Image Credits: AI Generated

DOI: 10.1007/s00122-026-05389-1

Keywords: durum wheat, wild emmer, QTL mapping, grain weight, grain size, recombinant inbred lines, marker-assisted breeding, SNP array, candidate genes, crop yield, genetic improvement, Triticum turgidum